NetGuardians, the award-winning Swiss FinTech, has joined forces with the School of Engineering and Management (HEIG-VD) of the University of Applied Sciences and Arts, Western Switzerland (HES-SO) on a project that will further improve NetGuardians’ machine learning and artificial-intelligence software for financial fraud detection and prevention.
The project is being funded by Innosuisse - the Swiss Innovation Agency.
The aim of the joint research project between NetGuardians and the Institute for Information and Communication Technologies (IICT), an interdisciplinary applied research body based at HEIG-VD, is to create an automated feedback loop using active learning algorithms. The goal is to further decrease the number of hits a bank needs to supervise for financial fraud prevention. A secondary objective is to explore different ways to use machine learning to further improve fraud detection.
Professor Stephan Robert of the IICT says: “It is so important that high value-added companies collaborate with academia on cutting-edge research to remain competitive and be able to bring effective solutions to market. I am very pleased to be working with NetGuardians on this project.”
Jérôme Bovay, NetGuardians data scientist, says: “Our aim is to develop more advanced machine-learning tools for banks, to further reduce false alerts and make our fraud-mitigation software even more efficient. It makes sense to incorporate active learning into our fraud-prevention models. The outcome of this project will make life harder for fraudsters and easier for those trying to prevent crime.”
Innosuisse says: “We have strict funding criteria which are: the innovative content of the project; the quality of the project planning; the competence of the project team members to implement the project and the project's contribution to sustainable development. The project application of NetGuardians and HEIG-VD fulfilled these criteria and therefore will be supported by Innosuisse.”
This is the second research project between NetGuardians and HEIG-VD. It follows a successful collaboration in 2017 looking into real-time fraud detection using machine learning.
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